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Company Info
AMAZON
Brisbane, CA, United States

Company Profile


SDE - BigData


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Job ID:

5365

Location:

Princeston, NJ, United States 

Category:

Analytics, Bi/BO, Big Data Analytics, Big Data Appliance Skills, Big Data Architect, Big Data BI, Big Data Developer, BigData Admininistration (DBA), BigData Visualization, C++ #, Consultant, Data Mining, Data Scientist, Information Technology, Java Developer, Machine Learning, NLP Programming, NoSql-Database, Pig, Predictive Analytics, Project Manager, Python, R Language, SAS, Software Engineering, SPSS, SQL, Statistics, Strategy-Planning
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Job Views:

293

Employment Type:

Full time

Posted:

06.12.2017
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Job Description:

High quality data is the foundation of building awesome user experiences. Now take the world’s largest product catalog and imagine how you could influence the experience for millions of customers on the world’s largest e-commerce site. Amazon’s Catalog Quality group (part of the search and discovery organization) is looking for an applied research scientist to help us make the world’s best product catalog even better. An information-rich and accurate product catalog is a strategic asset for Amazon. It powers unrivaled product discovery, informs customer buying decisions, offers a large selection and positions Amazon as the first stop for shopping online.

We use statistical and machine learning techniques to find out what matters most to our customers, to identify problems in the product data coming from millions of sellers and vendors, and to fix the most impactful problems at scale. We use machine learning to develop models that can extract missing data or fix inaccurate data automatically and drive efficient workflows allowing humans to apply their judgment when necessary. These problems are challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages), multitude of input sources (millions of sellers contributing product data with different quality), and complexity of the customer experience data (interaction across multiple devices and interaction points from search to purchase).
As a scientist on this team you will be on the leading edge of understanding how information within Amazon’s catalog affects our customers and help devise short term and long term strategy for enhancing the customer experience. You will have the opportunity to design new data analytical workflows at a scale rarely available elsewhere, utilizing a vast array of Amazon’s cloud computing technologies such as EMR and Redshift. You will apply your knowledge about data science by creating algorithmic solutions that combine clustering, pattern mining, predictive modeling, deep learning, and statistical testing and apply them to huge data amounts of data describing the products in the catalog and the customer interactions.

Job Requirements:

Responsibilities:
  • Analyze large amounts of Amazon’s business data to discover patterns, find anomalies, build models and derive insight and business value.
  • Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and scoring.
  • Work closely with software engineering teams to integrate data analysis workflows in production systems.
  • Produce compelling management reporting on a regular basis.
  • Participate in strategic analysis and help define the roadmap definition for the team.


Basic Qualifications
 
  • Master’s Degree in Computer science (Machine Learning, Data Mining, Statistics).
  • Able to formulate complex SQL queries and experience working with Business Intelligence tools.
  • Knowledge of scientific programming in scripting languages such as R/Python/Matlab.


Preferred Qualifications
 
  • PhD in Computer Science (Machine Learning, Data Mining, Statistics).
  • Ability to distill informal business requirements into problem definitions, dealing with ambiguity and competing objectives.
  • Ability to handle multiple competing priorities in a fast-paced environment
  • Extensive knowledge and practical experience in machine learning, data mining, artificial intelligence, statistics with track record of publications.
  • Experience in building automated analytical systems utilizing large data sets.
  • Experience with distributed algorithms (Map-Reduce, MPI).
  • Professional experience in software development (software design and development life cycle).
  • Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.



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